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RUSAL Implements Neural Networks to Improve Alumina Quality

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New Delhi, April 9, 2026: Global aluminium giant RUSAL has announced the successful industrial deployment of a proprietary neural network-based technology designed to control aluminium hydroxide particle fractions. This advanced digital solution, developed by the company’s Engineering Department, is currently operational at the decomposition unit of the RUSAL Kamensk-Uralsky alumina refinery, where it is already delivering measurable improvements in production quality and energy efficiency, the company said in a press release.

The technology targets the decomposition stage, a critical phase in the multi-step process of extracting alumina from bauxite ore. Because the quality of the decomposition intermediate directly dictates the quality of the final aluminium metal, precision at this stage is vital. The new system utilizes a digital twin of the decomposition process trained on 15 years of historical data. By analyzing the physical parameters of the preceding 120 days, the neural network generates a 90-day forecast of fractional composition with a remarkable error rate of less than 5%.

This high level of predictive accuracy allows for multi-parameter process optimization that was previously unattainable. According to the company, the system has already led to a 4.4% reduction in fine fraction content. By coarsening the alumina, the refinery has improved dry gas cleaning performance at its smelters and reduced the consumption of alumina, anodes, and electricity per tonne of metal produced. These technical gains directly support the company’s stated goals, as a representative noted that “energy efficiency and environmental sustainability remain central priorities for the company.”

The implementation marks a significant step forward in the use of artificial intelligence within the heavy industry sector. While RUSAL has previously integrated digital twins to optimize resource consumption, this new application represents a shift toward predictive and advisory control. By leveraging these proprietary algorithms, the company has managed to surpass comparable global solutions, enabling process engineers to make more informed adjustments to the decomposition batteries.

Through this digital transformation, RUSAL continues to align its industrial operations with modern technological standards, focusing on high-performance electrolysis and reduced environmental impact. The success at the Kamensk-Uralsky refinery serves as a benchmark for the company’s ongoing efforts to integrate AI-driven solutions across its global production chain to maintain a competitive edge in metal quality and operational sustainability.

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